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Post-Fire Behavior of Cold-Formed Steel Semi-Oval Hollow Stub Columns
https://orcid.org/0000-0001-8106-6949
This study deals with the compressive performance of cold-formed steel semi-oval hollow section (CFS-SOHS) stub columns after exposure to a standard fire. An experimental program was carried out on 17 CFS-SOHS stub columns after four different fire exposure temperatures, namely 300°C, 550°C, 750°C, and 900°C. Details of post-fire test specimens, material properties, stub column test arrangements, and results are described and discussed in this paper. A finite-element model was established and then validated by the experimental compressive performance in terms of ultimate strength, load-end shortening response, and failure mode. Parametric analyses were then performed on 160 post-fire CFS-SOHS stub column specimens to furnish more numerical data. The acquired experimental and numerical compressive strengths were compared against the design predictions by the direct strength method (DSM) initially calibrated for open sections, and the modified DSM initially proposed for CFS-SOHS without fire. A reliability analysis was performed. Comparisons show that the modified DSM offers accurate and reliable post-fire residual resistance predictions for CFS-SOHS stub columns after exposure to the standard fire.
Post-Fire Behavior of Cold-Formed Steel Semi-Oval Hollow Stub Columns
https://orcid.org/0000-0001-8106-6949
This study deals with the compressive performance of cold-formed steel semi-oval hollow section (CFS-SOHS) stub columns after exposure to a standard fire. An experimental program was carried out on 17 CFS-SOHS stub columns after four different fire exposure temperatures, namely 300°C, 550°C, 750°C, and 900°C. Details of post-fire test specimens, material properties, stub column test arrangements, and results are described and discussed in this paper. A finite-element model was established and then validated by the experimental compressive performance in terms of ultimate strength, load-end shortening response, and failure mode. Parametric analyses were then performed on 160 post-fire CFS-SOHS stub column specimens to furnish more numerical data. The acquired experimental and numerical compressive strengths were compared against the design predictions by the direct strength method (DSM) initially calibrated for open sections, and the modified DSM initially proposed for CFS-SOHS without fire. A reliability analysis was performed. Comparisons show that the modified DSM offers accurate and reliable post-fire residual resistance predictions for CFS-SOHS stub columns after exposure to the standard fire.
Post-Fire Behavior of Cold-Formed Steel Semi-Oval Hollow Stub Columns
https://orcid.org/0000-0001-8106-6949
This study deals with the compressive performance of cold-formed steel semi-oval hollow section (CFS-SOHS) stub columns after exposure to a standard fire. An experimental program was carried out on 17 CFS-SOHS stub columns after four different fire exposure temperatures, namely 300°C, 550°C, 750°C, and 900°C. Details of post-fire test specimens, material properties, stub column test arrangements, and results are described and discussed in this paper. A finite-element model was established and then validated by the experimental compressive performance in terms of ultimate strength, load-end shortening response, and failure mode. Parametric analyses were then performed on 160 post-fire CFS-SOHS stub column specimens to furnish more numerical data. The acquired experimental and numerical compressive strengths were compared against the design predictions by the direct strength method (DSM) initially calibrated for open sections, and the modified DSM initially proposed for CFS-SOHS without fire. A reliability analysis was performed. Comparisons show that the modified DSM offers accurate and reliable post-fire residual resistance predictions for CFS-SOHS stub columns after exposure to the standard fire.
Post-Fire Behavior of Cold-Formed Steel Semi-Oval Hollow Stub Columns
J. Struct. Eng.
Zuo, Wenkang (author) / Chen, Man-Tai (author) / Young, Ben (author)
2024-10-01
Article (Journal)
Electronic Resource
English
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